In the modern computing world, users routinely enter search requests into a variety of search engines to search for information on a given topic. An operator may enter search terms into a user interface for the search engine, such as a web browser, and the search engine may search and return a list of Universal Resource Locators (URL) associated with resources stored in various network accessible information sources, such as web servers for the Internet.
In response to such search requests, the search engine may return hundreds or even thousands of search results, including various URLs, documents or other resources. In an effort to organize search results for a user, techniques have been developed for ranking the search results and providing the search results to the user in the order of relevance to the given search request. Prior techniques have attempted to obtain various properties from located resources, such as metadata, and use those properties to determine a ranking of the relevance of individual resources to a search query. In many cases, however, metadata associated with various search results is incorrect or misleading. For example, incorrect data used by a ranking system leads to a poor ranking of the search results. Consequently, a user may be forced to review a number of irrelevant resources before the user comes to more relevant resources located by the search engine. Accordingly, there is a need for improved techniques for ranking search results for a search application with respect to these and other considerations.